Proceedings of the IEEE

Interactive classification: A technique for acquiring and maintaining knowledge bases

Tim Finin

October 1, 1986

The practical application of knowledge-based systems, such as expert systems, often requires maintaining large amounts of declarative knowledge. As a knowledge base (KB) grows in size and complexity, it becomes more difficult to maintain and extend. Even someone familiar with the knowledge domain, how it is represented in the KB, and the contents of the current KB may have severe difficulties updating it. Even if the difficulties can be tolerated, there is a very real danger that inconsistencies and errors may be introduced into the KB through the modification. This paper describes an approach to this problem using an interactive classifier. An interactive classifier uses the contents of the existing KB and knowledge about its representation to help the maintainer describe new KB objects. The interactive classifier will identify the appropriate taxonomic location for the newly described object and add it to the KB. The new object is allowed to generalize existing KB objects, enabling the system to learn more about them.

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Tags: agent, ai, classification, knowledge representation, ontology, taxonomy

Type: Article

Volume: 74

Number: 10

Note: DOI: 10.1109/PROC.1986.13642

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Google Scholar Citations: 19 citations